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README.md

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-TheStage AI - Inference Acceleration Stack
+# **TheStage AI Platform**
+
+Inference optimization for LLMs, diffusion, and voice. Self-hosted or cloud. Works on NVIDIA GPUs, Apple Silicon, and edge devices.
+
+**Links:**
+
+[Web App](https://app.thestage.ai/) • [Docs](https://docs.thestage.ai/) • [Hugging Face](https://huggingface.co/TheStageAI) • [X](https://x.com/TheStageAI) • [LinkedIn](https://www.linkedin.com/company/thestageai) • [Discord](mailto:sergey@thestage.ai) (request invite) • [Email](mailto:support@thestage.ai)
+
+---
+
+# **What is TheStage AI**
+
+TheStage AI is an inference optimization stack. It helps you compress, compile, and serve models. You keep control of the accuracy versus performance trade-off.
+
+---
+
+# **Products / Components**
+
+- [**ANNA (Automatic Neural Network Acceleration)**](https://docs.thestage.ai/qlip/docs/source/anna_api.html)
+    
+    Automated compression analysis under user-defined constraints (size, MACs, latency, memory). Outputs a QlipConfig for compile and serve.
+    
+- [**Qlip**](https://docs.thestage.ai/qlip/docs/source/index.html)
+    
+    Full-stack optimization and inference framework. Quantization, sparsification, and compilation for NVIDIA GPUs (Apple Silicon supported). Produces pre-compiled (non-JIT) artifacts with dynamic shapes and mixed precision. Triton-based serving.
+    
+- [**Elastic Models**](https://docs.thestage.ai/tutorials/source/elastic_transformers.html)
+    
+    Qlip-optimized models with S / M / L / XL performance tiers (availability varies). L/M/S may include quantization or pruning for faster inference.
+    
+- [**TheStage CLI**](https://docs.thestage.ai/platform/src/thestage-ai-cli.html)
+    
+    Manage projects, tokens, and hardware from the terminal. Launch/monitor jobs, rent instances, and stream logs.
+    
+- [**TheStage Platform**](https://app.thestage.ai/)
+    
+    Web UI and APIs for instances, models, and deployments. Includes the [**Playground**](https://app.thestage.ai/) to test Elastic Models, switch hardware, and compare tiers before deployment.
+    
+
+---
+
+# **Key features**
+
+- **Elastic Models with S/M/L/XL tiers per model** (choose cost, quality, and memory balance; availability varies).
+- **ANNA constraint-driven compression analysis** (outputs a QlipConfig for compile and serve).
+- **Qlip compiler and runtime** (pre-compiled engines; no runtime JIT; dynamic shapes; mixed precision).
+- **OpenAI-compatible HTTP serving** (deploy and scale models through a standard API).
+- **Playground to test models and hardware** (compare performance and tiers before deployment).
+- **Self-host or run in the cloud** (use your own infrastructure; keep data private).
+- **Hardware support: NVIDIA (incl. Jetson), Apple Silicon, and edge targets** (NPUs, DSPs, and MCUs per model).
+- **Comprehensive tutorials and documentation** (from setup to evaluation and production).
+
+---
+
+# **Quickstart**
+
+- Install CLI: `pip install thestage`
+- Set token: `thestage config set --api-token <YOUR_API_TOKEN>` (get it in the web app)
+- Use `elastic_models` in your code and choose a tier (S/M/L/XL). See Markdown version for a snippet.
+- Diffusion and voice examples are in the docs.
+
+---
+
+# **Serving**
+
+OpenAI-compatible API flow with Modal is documented (single- and multi-GPU).
+
+Start here: https://docs.thestage.ai/
+
+---
+
+# **Supported hardware**
+
+- NVIDIA GPUs (incl. Jetson where applicable)
+- Apple Silicon
+- Edge/embedded devices
+
+---